Abstract
Determining the size of an ontology that is automatically learned from text corpora is an open issue. In this paper, we study the similarity between ontology concepts at different levels of a taxonomy, quantifying in a natural manner the quality of the ontology attained. Our approach is integrated in a recently proposed method for language-neutral learning of ontologies of thematic topics from text corpora. Evaluation results over the Genia and the Lonely Planet corpora demonstrate the significance of our approach.
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Zavitsanos, E., Petridis, S., Paliouras, G., Vouros, G.A. (2008). Learning Ontologies of Appropriate Size. In: Darzentas, J., Vouros, G.A., Vosinakis, S., Arnellos, A. (eds) Artificial Intelligence: Theories, Models and Applications. SETN 2008. Lecture Notes in Computer Science(), vol 5138. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87881-0_29
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DOI: https://doi.org/10.1007/978-3-540-87881-0_29
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87880-3
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